Center for Gastrointestinal Research, Center for Translational Genomics and Oncology, Baylor Scott & White Research Institute, Charles A Sammons Cancer Center, Baylor University Medical Center, Dallas, Texas, USA.
Department of Gastrointestinal Surgery, Tokyo Medical and Dental University Graduate School of Medicine, Tokyo, Japan.
Int J Cancer. 2020 Dec 1;147(11):3250-3261. doi: 10.1002/ijc.33129. Epub 2020 Jul 13.
Risk stratification in Stage II and III colorectal cancer (CRC) patients is critical, as it allows patient selection for adjuvant chemotherapy. In view of the inadequacy of current clinicopathological features for risk-stratification, we undertook a systematic and comprehensive biomarker discovery effort to develop a risk-assessment signature in CRC patients. The biomarker discovery phase examined 853 CRC patients, and identified a gene signature for predicting recurrence-free survival (RFS). This signature was validated in a meta-analysis of 1212 patients from nine independent datasets, and its performance was compared against established prognostic signatures and consensus molecular subtypes (CMS). In addition, a risk-prediction model was trained (n = 142), and subsequently validated in an independent clinical cohort (n = 286). As a result, this mesenchymal-associated transcriptomic signature (MATS) identified high-risk CRC patients with poor RFS in the discovery (hazard ratio [HR]: 1.79), and nine validation cohorts (HR: 1.86). In multivariate analysis, MATS was the most significant predictor of RFS compared to established prognostic signatures and CMS subtypes. Intriguingly, MATS robustly identified CMS4-subtype in multiple CRC cohorts (AUC = 0.92-0.99). In the two clinical cohorts, MATS stratified low and high-risk groups with a 5-year RFS in the training (HR: 4.11) and validation cohorts (HR: 2.55), as well as predicted response to adjuvant therapy in Stage II and III CRC patients. We report a novel prognostic and predictive biomarker signature in CRC, which is superior to currently used approaches and have the potential for clinical translation in near future.
在 II 期和 III 期结直肠癌(CRC)患者中进行风险分层至关重要,因为它可以选择辅助化疗的患者。鉴于当前临床病理特征在风险分层方面的不足,我们进行了系统而全面的生物标志物发现工作,以开发 CRC 患者的风险评估特征。在生物标志物发现阶段,我们检查了 853 例 CRC 患者,并确定了预测无复发生存率(RFS)的基因特征。该特征在来自 9 个独立数据集的 1212 例患者的荟萃分析中得到验证,并将其性能与既定的预后特征和共识分子亚型(CMS)进行了比较。此外,我们还训练了风险预测模型(n = 142),并随后在独立的临床队列(n = 286)中进行了验证。结果,这种间充质相关转录组特征(MATS)在发现队列(危险比[HR]:1.79)和 9 个验证队列(HR:1.86)中识别出了 RFS 较差的高风险 CRC 患者。在多变量分析中,与既定的预后特征和 CMS 亚型相比,MATS 是 RFS 的最显著预测因子。有趣的是,MATS 在多个 CRC 队列中稳健地识别出了 CMS4 亚型(AUC = 0.92-0.99)。在两个临床队列中,MATS 将低风险和高风险组分层,在训练队列中 5 年 RFS(HR:4.11)和验证队列(HR:2.55),并预测了 II 期和 III 期 CRC 患者对辅助治疗的反应。我们报告了一种新的 CRC 预后和预测生物标志物特征,该特征优于目前使用的方法,并且具有在不久的将来进行临床转化的潜力。